# used libraries
if (!require("ggplot2")) install.packages("ggplot2")
if (!require("plotly")) install.packages("plotly")
# R package DT provides an R interface to the JavaScript library DataTables.
if (!require("DT")) install.packages("DT")
# geom_mark_hull
if (!require("concaveman")) install.packages("concaveman")
if (!require("ggforce")) install.packages("ggforce")
This document is essentially a brief notes of the book above.
library(ggplot2)
mpg
Exploratory Data Analysis with Static plots
library(ggplot2)
ggplot(mpg, aes(displ, hwy)) + geom_point()
What are max hwy? ’Outliers`?
library(plotly)
p <- ggplot(mpg, aes(displ, hwy)) + geom_point()
ggplotly(p)
What are those models:
library(plotly)
m <- highlight_key(mpg)
p <- ggplot(m, aes(displ, hwy)) + geom_point()
gg <- highlight(ggplotly(p), "plotly_selected")
crosstalk::bscols(gg, DT::datatable(m))
## Setting the `off` event (i.e., 'plotly_deselect') to match the `on` event (i.e., 'plotly_selected'). You can change this default via the `highlight()` function.
Final figure:
ggplot(mpg, aes(displ, hwy)) +
geom_point() +
ggforce::geom_mark_hull(aes(filter = model == "corvette", label = model)) +
labs(
title = "Fuel economy from 1999 to 2008 for 38 car models",
caption = "Source: https://fueleconomy.gov/",
x = "Engine Displacement",
y = "Miles Per Gallon"
)
Interactions:
library(plotly)
p <- ggplot(mpg, aes(displ, hwy,color=model)) + geom_point()
ggplotly(p)